Network Modeling for Epidemics II
Meeting Times:
- Wednesday, July 23, 1:30 PM – 5:00 PM
- Thursday July 24, 9:00 AM – 5:00 PM
- Friday July 25, 9:00 AM – 5:00 PM
Classroom: TBA
Module Summary:
Network Modeling for Epidemics II extends the material in NME-I to developing research-level applications of EpiModel and its underlying TERGM statistical framework. Here, we focus on learning how to use the application programming interface (API) in EpiModel to design and program epidemic model components (or “modules”) that define a network-based epidemic model for a specific research question. The goal is to enable students to build EpiModel extensions to represent any infectious disease components in a system of interest.
This intermediate course will cover more advanced methods, such as working with multi-layer networks that represent different types of contacts (e.g., home and community) within the same population. We also demonstrate the process of working with egocentric network data, an inexpensive sample survey data collection design, to specify an epidemic model. Examples will cover the whole workflow: from conceptualization and data collection to estimation and simulation in EpiModel.
NME-II utilizes multiple learning approaches: collective exercises to design and build a complex, disease-specific network-based epidemic model; lab work to design specific epidemic module components from demographics to prevention interventions; and individual consultations on students’ own network-based epidemic modeling projects.
Prerequisites:
We strongly suggest Network Modeling for Epidemics I at SISMID (or one of the prior NME weeklong workshops at the University of Washington). Please contact one of the instructors in advance if you feel like you can skip NME-I based on prior experience/expertise. We also strongly encourage students to bring their own network data set/project if they have one (but we will provide one for those who don’t) and prepare specific modeling-related research questions for their infectious disease of interest.
Module Content:
- Extending EpiModel using the module building API to represent specific infectious disease processes and answer specific research questions
- Using the EpiModel Gallery as templates for EpiModel extensions
- Working with real-world network data as inputs for EpiModel, from collection to descriptive analysis and epidemic model parameterization
- Conceptualizing and implementing appropriate network parameterizations for different infectious disease systems and research questions
- Multi-layer networks (overlapping contact types on the same node set) in EpiModel
- Practice conceptualizing a full-scale HIV/STI extension model, from start to finish
- Directed lab exercise to build out a SARS-CoV-2 epidemic model in EpiModel from the basic SIR template
- Extended time to consult with students on network data analysis with TERGMs and epidemic modeling with EpiModel
Instructors
Samuel Jenness, PhD
Associate Professor, Department of Epidemiology, Emory University
Samuel Jenness, PhD MPH is an Associate Professor in the Department of Epidemiology at Emory University. He is the Principal Investigator of the EpiModel Research Lab, which uses epidemiological and economic modeling approaches to understand the dynamics of sexually transmitted and respiratory infectious diseases. Recent studies have investigated the co-circulation of multiple infectious pathogens and optimizing the scale-up of prevention interventions to reduce health disparities.
His methodological research has led to the development of an open-source software platform, EpiModel, which allows users to build and simulate data-driven mechanistic models for infectious disease dynamics that integrate network data and models.
Martina Morris, PhD
Professor Emerita, Department of Statistics and Department of Sociology, University of Washington
Dr. Morris is a sociologist with an interest in the analysis of social structure and population dynamics. Her research is interdisciplinary, intersecting with demography, economics, epidemiology and public health, and statistics. Examples from her current projects include the study of partnership networks in the spread of HIV/AIDS, the impact of economic restructuring on inequality and mobility, and the development of Relative Distribution methods for statistical analysis.
Steve Goodreau, PhD
Professor, Department of Anthropology, University of Washington
Dr. Goodreau's research interests are in the use of network modeling and network data to explore the epidemiology of HIV and other STIs. He is a co-developer of the statnet and EpiModel suites for network epidemic modeling. He has published on behavioral and clinical drivers of HIV disparities, as well as on assessments of interventions, primarily among communities of men who have sex with men, both domestically and internationally. His current work also explores behavioral and clinical impacts on HIV viral evolution.
Required Software:
We will be using the R statistical programming language throughout. Within R, users will install EpiModel and the related Statnet suite of packages for network analysis.
Recommended Reading:
Prior to the course, we recommend students review the materials on this page: https://epimodel.io/0_nme_prep/reading.html.
